The below scatterplot shows the correlation between WHO (x-axis) estimates and IHME (y-axis) estimates, with each point colored by its (WHO-defined) region.

We can also fit each region's line of best fit.

We can also examine relative difference in estimates, by WHO region. TIn the below violin charts, the jittered points represent each country.

The above metric of relative variance is independent of which source is higher. Here, we visualize variance by examining the ratio of IHME deaths over WHO deaths.

For ease of interpretation, we remove those outliers.

As a complement to the above, we can also examine the ratio of WHO deaths over IHME deaths.

In the below chart we identify those countries for whom the ratio of IHME-estimated deaths (TB + HIV/TB) is greatest (top 10) and least (bottom 10).

As a complement to the above, we can examine the inverse: WHO deaths over IHME deaths.

Rather than ratios, we can also examine absolute differences. The below bar chart shows those countries with the greatest absolute difference (IHME estimated deaths minus WHO estimated deaths).

As a complement to the above, we can do WHO deaths minus IHME deaths.

All of the above are biased by small numbers (ie, countries with very few cases are most likely to have the most extreme ratios). Accordingly, we can instead examine an indicator suggested by Frank: The number of reported cases, divided by deaths.

This indicator is, in fact, two indicators. One is the reported cases divided by deaths (per the WHO), and the other is per the IHME. The below histograms show the country-specific distribution of these indicators.

Here is the distribution of the cases over deaths indicators.

When we examine the cases over deaths metrics at the country specific level as well. As per before, we'll take the top and bottom 10 countries only.

The below chart shows the estimated percentage of new TB cases with rifampicin resistant TB (x-axis) and the cases per WHO deaths (y-axis):

The below chart is identical, but using IHME deaths rather than WHO.

We can also examine the same x-axis (resistance), but relative to other indicators.

IHME

WHO

Above 0 means that the WHO estimates n percentage higher than the IHME. Vice-versa.

In the previous chart, it may seem that there are no negative values. This is not the case. It's simply that when the WHO and IHME differ in the extremes, it pulls in one direction:

WHO minus IHME instead of WHO divided by IHME.

The previous map may appear overwhelmingly green (ie, that most of the countries have a near 0 difference). This is due to a difference in scale (ie, very few extreme observations). We can get a more granular look at things by taking the quadratic root of our indicator (next).